LC-ESI-MS/MS-Based Comparative Metabolomic Study, Antioxidant and Antidiabetic Activities of Three Lobelia Species: Molecular Modeling and ADMET Study

Abstract

The hydroethanol (70%) extracts of three Lobelia species (L. nicotianifolia, L. sessilifolia, and L. chinensis) were analyzed using LC-ESI-MS/MS. Forty-five metabolites were identified, including different flavonoids, coumarin, polyacetylenes, and alkaloids, which were the most abundant class. By applying Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) based on LC-ESI-MS/MS analysis, the three species were completely segregated from each other. In addition, the three Lobelia extracts were tested for their antioxidant activities using a DPPH assay and as antidiabetic agents against αglycosidase and α-amylase enzymes. L. chinensis extract demonstrated significant antioxidant activity with an IC50 value of 1.111 mg/mL, while L. nicotianifolia showed mild suppressing activity on the α-glycosidase activity with an IC50 value of 270.8 μg/mL. A molecular simulation study was performed on the main compounds to predict their potential antidiabetic activity and pharmacokinetic properties. The molecular docking results confirmed the αglycosidase inhibitory activity of the tested compounds, as seen in their binding mode to the key amino acid residues at the binding site compared to that of the standard drug acarbose. Furthermore, the predictive ADMET results revealed good pharmacokinetic properties of almost all of the tested compounds. The biological evaluation results demonstrated the promising activity of the tested compounds, aligned with the in silico results.